An expert system makes decisions or solves problems in a particular field by using knowledge and analytical rules. For one early example, Cambell Soup Company created over 150 rules to run the complex soup sterilizers that kill bacterial in canned soup. See Artificial Intelligence, by Time-Life Books, 1986, pages 36-43. It took approximately 14 man-months to define these over 150 rules.
Additionally, design optimization is often performed using multiple criteria optimization, also known as objective function optimization. For one early example, the very successful Ford Taurus™ was designed by optimizing over 400 criteria that directly affected the senses of the user. See Juran on Quality by Design, 1992, page 465.
There are at least 3 distinct aspects to design optimization. The first aspect is to create or discover or define a set of criteria (factors) that are of interest. The second aspect is to assign an objective value or cost (or constraining limits) to each criterion. The third aspect is to search for the optimum design (maximize value or minimize cost). None of these aspects are trivial. For example, an objective function defining the quality of a car might simultaneously consider gas mileage, and engine power. These two factors (mileage and power) interact in complex and non-linear ways.
Power distribution systems are complex systems in many respects: multiple sources of power, multiple power consuming devices, and multiple power paths to distribute power from one specific power source to a specific power consuming device.
Another source of complexity is caused by sources of power and consumers of power that change over time. For example, one source of power may stop producing power (a generator may be hit by a missile), or one power consuming device may stop consuming power (a radar may be turned off). Similarly, sources and consumers may be added to the system.
Even after an optimal power distribution configuration is determined, a third source of complexity is determining an optimal transition path to travel in order to reach the optimal configuration. These optimizations (optimal configuration and optimal transition path) are multiple criteria optimizations, and thus require sets of rules to define an objective criteria function that must be optimized (either maximized or minimized, depending upon the form of the function). The objective criteria function is generally treated as a cost function and minimized. The cost of transiting from a first state A to a second state B might not equal the cost of transiting in the reverse direction. In other words, the transition costs between two states may depend on the direction of the transition.
Additionally, directly transitioning from a non-optimal configuration to an optimal configuration (without any intermediate configurations) is often not possible. Further, even if a direct transition is possible, the direct transition may not be the optimal transition path.
Some power distribution systems are very time sensitive. For example, if power to a defensive radar on a military ship is lost for a few seconds, then the ship may be destroyed by a missile. A heart pump in a hospital may have similar time sensitive needs.
Thus, there is a need for a expert power distribution system that determines an optimal power distribution configuration, and determines an optimal transition path to reach said optimal power configuration.
The following patents and patent publications describe the state of the art: U.S. Pat. No. 5,349,644 by Massey et al., U.S. Pat. No. 5,629,862 by Brandwain et al., U.S. Pat. No. 5,936,318 by Weiler et al., U.S. Pat. No. 6,459,175 by Potega, U.S. Pat. No. 6,633,802 by Sodeski et. al., U.S. Pat. No. 6,921,987 by Marin-Martinod, U.S. Patent Application Publication 2003/0023885 by Potter, U.S. Patent Application Publication 2004/0254688 by Chassin, and U.S. Patent Application Publication 2005/0038571 by Brickfield.